Most companies don’t have an ETL problem — they have an ownership problem. Pipelines get written by whoever needed the data first: an analyst’s Python script, a no-code chain someone set up in a hurry, a cron job on a laptop. It works, until that person changes teams and the only documentation is a Slack thread from last March.
ETL-as-a-Service means we take the whole layer off your plate. Connectors to your sources — SaaS APIs, production databases, flat files, event streams — transformation logic in version control, tested and documented, running inside your own cloud accounts with monitoring, alerting, and a named engineer who picks up when something breaks. You get a defined SLA and a predictable monthly cost instead of a growing pile of scripts with a bus factor of one.
Key Features
API, Database & File Connectors
Bring-Your-Own-Cloud Deploy
Git-Backed Transformations
CI/CD for Pipelines
Incremental Sync
Monitoring & Alerting
Defined SLA & Support Window
Full Documentation Handover
Key Advantages
Handoff-Ready From Day One
Documented, tested, and genuinely yours. When you build an in-house data team later, they inherit something clean — not a rescue project.
Runs Inside Your Cloud
Bring-your-own-cloud deployment on AWS, GCP or Azure. Your data never leaves your accounts — we operate inside them.
Someone Owns It
A named engineer, an agreed SLA, and monitored pipelines. Not a script whose only expert left the company.
One Predictable Line Item
A fixed monthly engagement instead of surprise contractor invoices or the cost and lead time of a full-time hire.
Everything in Version Control
Git-backed transformations with code review and CI. Every change is traceable, reviewable, and revertable.
No Per-Row Pricing Working Against You
Built on open tooling you own, so your bill scales with your infrastructure — not with a vendor's row counter.
Trusted by Innovators Across Industries
The data engineering work happens underneath: pipelines that are clean, tested, and production-grade, so the AI layer on top actually holds up. That's the difference between a chatbot that impresses in a demo and an agent your team can put into a real workflow.
What Our Clients Say
Trusted by global enterprises and fast-growing startups to deliver reliable, scalable, and intelligent data solutions.
Frequently Asked Questions
Here are some of the most common questions we receive from businesses exploring our solutions.
What kind of data do you work with?
We handle structured, semi-structured, and unstructured data from various sources, including databases, APIs, files, IoT devices, and streaming platforms.
Can you work in our cloud environment?
Yes, with our Bring Your Own Cloud (BYOC) model, we build and manage data pipelines securely within your existing cloud infrastructure.
What visualizations or reports can you deliver?
We create interactive dashboards and visual reports using tools like Power BI, Tableau, or custom-built frontends tailored to your KPIs.
Is your service scalable as our data grows?
Yes, all our solutions are cloud-native and built to scale with your data volume, user base, and business complexity.
See Our Work in Action
Watch how we transform raw data pipelines into actionable dashboards, with AI agents enabling real-time insights.
AI Agents & LLM Apps Built to Run in Production
Most AI agents fail quietly - on stale data, broken pipelines, or retrieval that returns the wrong context. GKCodeLabs builds AI agents, RAG systems, and LLM applications on data infrastructure we engineer ourselves - so what you ship holds up under real traffic, not just demos.